# beast mit Homebrew installieren

Prüfe Installationswege, Executables, Metadaten und Sicherheitshinweise für beast in AI-Agent-Workflows.

## Installation

```sh
sudo av install brew:beast
```

Weitere Installationsbefehle:

### macOS

- Homebrew (100%):

```sh
brew install beast
```

  Evidenz: local Homebrew formula metadata

## Paketfakten

- **Paketschlüssel:** brew:beast
- **Paketmanager:** Homebrew
- **Version:** 10.5.0
- **Quellzusammenfassung:** Bayesian Evolutionary Analysis Sampling Trees
- **Homepage:** <https://beast.community/>
- **Repository:** <https://github.com/beast-dev/beast-mcmc>
- **Zuletzt aktualisiert:** 2026-05-20T10:15:39Z
- **Generiert:** 2026-08-03T19:37:03+00:00

## Executables

- beast (Alias)
- beauti (Alias)
- loganalyser (Alias)
- logcombiner (Alias)
- treeannotator (Alias)
- treestat (Alias)

## Installationsverhalten

- Bottle: nicht verfügbar

## Version und Aktualität

- Seite generiert: 2026-08-03
- Manager-Version: 10.5.0
## Projektgeschichte und Nutzung

BEAST is Bayesian Evolutionary Analysis Sampling Trees, a scientific software package for Bayesian phylogenetic analysis of molecular sequences using MCMC.

### Projektgeschichte

The official documentation describes BEAST as focused on rooted, time-measured phylogenies, strict or relaxed molecular-clock models, coalescent population models, and Bayesian model testing.

The official About page credits Alexei J. Drummond, Andrew Rambaut, and Marc A. Suchard as designers and developers, with a large contributor and institutional-support history across evolutionary-analysis research.

### Adoptionsgeschichte

BEAST's adoption is primarily academic and scientific rather than general developer tooling. The official README distributes binaries for Mac, Windows, and UNIX/Linux and the Homebrew package exposes the command-line programs for Unix package users.

The supplied Homebrew metadata includes executables such as beast, beauti, loganalyser, logcombiner, treeannotator, and treestat, reflecting the suite-style workflow used to set up analyses, run MCMC, and inspect results.

### Wie es verwendet wird

Typical BEAST workflows use BEAUti to prepare XML analysis files, beast to run Bayesian MCMC analyses, and companion tools such as LogAnalyser, LogCombiner, TreeAnnotator, and TreeStat to inspect or summarize outputs.

The package is Java-based and cross-platform, but the Homebrew formula makes its command-line tools available in the same way as other scientific CLI suites.

### Warum Paket-Nerds sich dafür interessieren

BEAST is significant as a package because it brings a full research-grade phylogenetics suite into package-manager workflows. It is not a small Unix filter, but Homebrew makes the JVM-backed analysis tools installable and scriptable beside other scientific software.

### Zeitleiste

- 2015: The official GitHub repository for beast-mcmc was created.
- 2016: The GitHub releases include BEAST v1.8.4.
- 2018: The GitHub releases include BEAST v1.10.4, identified by the README as the previous major release.
- 2025: The GitHub releases include BEAST X v10.5.0.
- 2026: The official site and repository continue to describe BEAST X and recent beta releases.

### Related projects

- BEAUti, LogAnalyser, LogCombiner, TreeAnnotator, and TreeStat are bundled companion programs in the BEAST workflow.
- BEAST 2 is a related project in the broader BEAST ecosystem, but this Homebrew package points at the beast-mcmc repository and BEAST X documentation.

### Quellen

- <https://beast.community/>
- <https://beast.community/about>
- <https://github.com/beast-dev/beast-mcmc#readme>
- <https://github.com/beast-dev/beast-mcmc/releases>
- input.json source_facts.executables


## Sicherheitshinweise

Für beast wurde kein passendes lokales Secret-Handling-Manifest gefunden. Nucleus-Paketmetadaten bleiben hier veröffentlicht, damit künftige Abdeckung eine stabile Paket-URL hat.



## Combined YAML source

View the package source record on GitHub. [combined/beast.yml](https://github.com/mxcl/pkgdb/blob/main/combined/beast.yml)


## Quellen

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- cross-ecosystem install command graph